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Anyi Wang

2 accepted papers

2025

Improving LLM Reasoning through Interpretable Role-Playing Steering

EMNLP 2025

Role-playing has emerged as an effective technique for enhancing the reasoning capabilities of large language models (LLMs). However, existing methods primarily rely on prompt engineering, which often lacks stability and interpretability. In this paper, we introduce Sparse Autoencoder Role-Playing S

Cited by 0SourcePDFScholar
2025

What’s the Difference? Supporting Users in Identifying the Effects of Prompt and Model Changes Through Token Patterns

ACL 2025long

Prompt engineering for large language models is challenging, as even small prompt perturbations or model changes can significantly impact the generated output texts. Existing evaluation methods of LLM outputs, either automated metrics or human evaluation, have limitations, such as providing limited…